From the knowledge gathered through conversations with Hy5-partnered certified orthotist / prosthetists (CPOs), as well as her own academic background, the IA composed an initial summarizing report on the current state of socket creation, along with the considerations and cautions for digitizing the socket creation process. From this distillation, the IA worked with senior management to put together a plan of action for the project. As the CPO feedback to the original project plan also highlighted significant challenges, these were also taken under consideration. From the IA’s findings and CPO feedback, it became apparent that developing a scanning algorithm to the quality that is required for this application was beyond the timeline of the project, the management greenlighted a thorough testing plan of external scanning resources toward use in the DigiSocket project. The IA then developed an experimental plan towards identifying an existing mobile scanning phone application that would be compatible with scanning residual limbs in varying conditions with high accuracy. The IA also developed an initial schematic for marking the residual limb such that the subcutaneous bony morphology and pressure points would be apparent in the 3D digital model.
The IA compiled a long list of existing phone scanning apps was assessed for basic technical experimental protocol to determine the quality of the scans on complete limbs, particularly the algorithm adjustments for skin and body hair. The long list of scanning phone apps was pared down to a short list for full experimental testing on residual limbs. The experimental testing of various existing mobile phone scanning applications took place over the course of several months. This iterative testing approach involved a variety of experimental conditions to assess scanning performance across different lighting conditions, skin types, users, external limb covers, phone cameras, limb morphology marking techniques, and limb sizes. The apps were also graded on their scan output file format, as the 3D model and associated texture file had to be compatible with Hy5 modelling systems. From the extensive testing described above, one phone app stood out as the most suitable scanning solution. This app was available across phone operating systems, and met the testing requirements for flexibility in accommodating various scanning environmental conditions and patient variability. Its algorithm is already used in facial scanning, so meets the topographical resolution requirements for prosthetic socket development. The experimental testing resulted in ‘best practices’ recommendations for residual limb scanning. These include placing a white or light-coloured sock over the residual limb prior to marking the bony morphology and pressure points, scanning in a well-lit room to minimize shadowing on the limb, and moving at a consistent distance around the surface of the residual limb during image capture, among others, which have been fully summarized in internal Hy5 documentation. Finally, the project concluded with scan post-processing protocol development towards creation of a 3D digital model.
